RT Journal Article
T1 On the participation of energy storage systems in reserve markets using Decision Focused Learning
A1 Paredes-Parrilla, Ángel
A1 Toubeau, Jean-François
A1 Aguado-Sánchez, José Antonio
A1 Vallée, François
K1 Ingeniería eléctrica
K1 Energía - Almacenamiento
AB Battery Energy Storage Systems (BESSs) are particularly well-suited to deepen the decarbonisation of reserve markets, traditionally dominated by non-renewable generators. BESSs operators often rely on Predict-Then-Optimise (PTO) methods to participate in these markets, which focus on forecasting market conditions without directly considering the impact of subsequent decisions during training. Recently, learning models have evolved to incorporate decision outcomes during training, known as Decision Focused Learning (DFL) methodologies, which have the potential to increase market benefits. This paper introduces a DFL approach that integrates the decision-making process of BESSs when participating in reserve markets into the training of their predictive models. By expressing the optimisation problem as a primal–dual mapping using the Karush–Kuhn–Tucker (KKT) conditions, the proposed DFL method enables the regressor to learn from the BESS’s decisions, refining its predictions based on observed outcomes, improving decision accuracy and market performance. Results show that the proposed DFL approach outperforms traditional PTO methods, with up to a 9.5% increase in profits for a case study based on the Belgian secondary reserve market, highlighting its effectiveness in managing the complexities of dynamic market conditions.
PB Elsevier
SN 2352-4677
YR 2025
FD 2025-03-13
LK https://hdl.handle.net/10630/38516
UL https://hdl.handle.net/10630/38516
LA eng
NO Paredes, Á., Toubeau, J. F., Aguado, J. A., & Vallée, F. (2025). On the participation of energy storage systems in reserve markets using Decision Focused Learning. Sustainable Energy, Grids and Networks, 42, 101677. https://doi.org/10.1016/J.SEGAN.2025.101677
NO Funding for open access charge: Universidad de Málaga / CBUA
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026